arXiv subjects

Ali Hürriyetoğlu

Publications and source records attributed to Ali Hürriyetoğlu.

22 records · Page 2Linked to original sources

arXiv2020

Cross-context News Corpus for Protest Events related Knowledge Base Construction

We describe a gold standard corpus of protest events that comprise of various local and international sources from various countries in English. The corpus contains document, sentence, and token level annotations. This corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-related information, constructing knowledge bases which enable comparative social and political science studies. For each news source, the annotation starts on random samples of news articles and continues with samples that are drawn using active learning. Each batch of samples was annotated by two social and political scientists, adjudicated by an annotation supervisor, and was improved by identifying annotation errors semi-automatically. We found that the corpus has the variety and quality to develop and benchmark text classification and event extraction systems in a cross-context setting, which contributes to the generalizability and robustness of automated text processing systems. This corpus and the reported results will set the currently lacking common ground in automated protest event collection studies.

cs.CL↗

arXiv2020

Tense, aspect and mood based event extraction for situation analysis and crisis management

Nowadays event extraction systems mainly deal with a relatively small amount of information about temporal and modal qualifications of situations, primarily processing assertive sentences in the past tense. However, systems with a wider coverage of tense, aspect and mood can provide better analyses and can be used in a wider range of text analysis applications. This thesis develops such a system for Turkish language. This is accomplished by extending Open Source Information Mining and Analysis (OPTIMA) research group's event extraction software, by implementing appropriate extensions in the semantic representation format, by adding a partial grammar which improves the TAM (Tense, Aspect and Mood) marker, adverb analysis and matching functions of ExPRESS, and by constructing an appropriate lexicon in the standard of CORLEONE. These extensions are based on iv the theory of anchoring relations (Temürcü, 2007, 2011) which is a crosslinguistically applicable semantic framework for analyzing tense, aspect and mood related categories. The result is a system which can, in addition to extracting basic event structures, classify sentences given in news reports according to their temporal, modal and volitional/illocutionary values. Although the focus is on news reports of natural disasters, disease outbreaks and man-made disasters in Turkish language, the approach can be adapted to other languages, domains and genres. This event extraction and classification system, with further developments, can provide a basis for automated browsing systems for preventing environmental and humanitarian risk.

cs.CL↗

arXiv2020

Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report

We describe our effort on automated extraction of socio-political events from news in the scope of a workshop and a shared task we organized at Language Resources and Evaluation Conference (LREC 2020). We believe the event extraction studies in computational linguistics and social and political sciences should further support each other in order to enable large scale socio-political event information collection across sources, countries, and languages. The event consists of regular research papers and a shared task, which is about event sentence coreference identification (ESCI), tracks. All submissions were reviewed by five members of the program committee. The workshop attracted research papers related to evaluation of machine learning methodologies, language resources, material conflict forecasting, and a shared task participation report in the scope of socio-political event information collection. It has shown us the volume and variety of both the data sources and event information collection approaches related to socio-political events and the need to fill the gap between automated text processing techniques and requirements of social and political sciences.

cs.CL↗

arXiv2016

Unraveling reported dreams with text analytics

We investigate what distinguishes reported dreams from other personal narratives. The continuity hypothesis, stemming from psychological dream analysis work, states that most dreams refer to a person's daily life and personal concerns, similar to other personal narratives such as diary entries. Differences between the two texts may reveal the linguistic markers of dream text, which could be the basis for new dream analysis work and for the automatic detection of dream descriptions. We used three text analytics methods: text classification, topic modeling, and text coherence analysis, and applied these methods to a balanced set of texts representing dreams, diary entries, and other personal stories. We observed that dream texts could be distinguished from other personal narratives nearly perfectly, mostly based on the presence of uncertainty markers and descriptions of scenes. Important markers for non-dream narratives are specific time expressions and conversational expressions. Dream texts also exhibit a lower discourse coherence than other personal narratives.

cs.CL↗